Research on the Spatiotemporal Patterns of Ecosystem Services and Urban Sustainable Development: A Case Study of the “Mid-Spine Belt of Beautiful China”

Abstract

Urban sustainable development relies on stable ecosystem services (ESs) to coordinate human activities and natural ecosystems. This article takes the “Mid‑Spine Belt of Beautiful China” as the study area,using the entropy weight method and the InVEST model, combined with multi-source data such as remote sensing, geographic, and statistical data, to quantify three categories of Sustainable Development Goal11 (economic, social, environmental) and four types of ESs (carbon storage,water yield, soil conservation, vegetation cover); establishing an evaluation framework for sustainable development applicable to the “Mid-Spine Belt of Beautiful China”. From 2015 to 2023, regional SDG11 rose generally with the lowest score in 2021; inter-city gaps shrank but regional imbalance remained. Water yield and soil conservation declined yearly, while carbon storage and vegetation coverage kept growing. Spearman correlation and MGWR uncover obvious spatial heterogeneity in the synergy and trade-off between SDG11 and ESs: four synergy pairs and three trade-off pairs declined, and economic SDGs had the strongest negative link with vegetation coverage. SOM clustering divides the study zone into four differentiated subregions with distinct ES and SDG11 performances.This work has important practical significance for maintaining the stability and sustainable development of the “Mid-Spine Belt of Beautiful China” ecosystem.